Why data visualization matters

Let's say you need to understand thousands or even millions of rows
of data, and you have a short time to do it in. The data may come
from your team, in which case perhaps you're already familiar
with what it's measuring and what the results are likely to be. Or it
may come from another team, or maybe several teams at
once, and be completely unfamiliar. Either way, the reason you're
looking at it is that you have a decision to make, and you want to be
informed by the data before making it. Something probably hangs in
the balance: a customer, a product, or a profit.

How are you going to make sense of all that information efficiently
so you can make a good decision? Data visualization is an important
answer to that question.

However, not all visualizations are actually that helpful. You may
be all too familiar with lifeless bar graphs, or line graphs made with
software defaults and couched in a slideshow presentation or lengthy
document. They can be at best confusing, and at worst misleading. But
the good ones are an absolute revelation.

The best data visualizations are ones that expose something
new about the underlying patterns and relationships contained
within the data. Understanding those relationships — and being
able to observe them — is key to good decision making. The
Periodic Table is a classic testament to the potential of
visualization to reveal hidden relationships in even small datasets.
One look at the table, and chemists and middle school students alike
grasp the way atoms arrange themselves in groups: alkali metals, noble
gasses, halogens.

If visualization done right can reveal so much in even a small dataset like this, imagine what it can reveal within terabytes or petabytes of information.

Types of visualization

It's important to point out that not all data visualization is
created equal. Just as we have paints and pencils and chalk and film
to help us capture the world in different ways, with different
emphases and for different purposes, there are multiple ways in which
to depict the same dataset.

Or, to put it another way, think of visualization as a new set of
languages you can use to communicate. Just as French and Russian and
Japanese are all ways of encoding ideas so that those ideas can be
transported from one person's mind to another, and decoded
again — and just as certain languages are more conducive to
certain ideas — so the various kinds of data visualization are a
kind of bidirectional encoding that lets ideas and
information be transported from the database into your brain.

Explaining and exploring

An important distinction lies between visualization for
exploring and visualization for explaining. A third
category, visual art, comprises images that encode data but
cannot easily be decoded back to the original meaning by a
viewer. This kind of visualization can be beautiful, but it is not
helpful in making decisions.

Visualization for exploring can be imprecise. It's useful when
you're not exactly sure what the data has to tell you and you're
trying to get a sense of the relationships and patterns contained
within it for the first time. It may take a while to figure out how
to approach or clean the data, and which dimensions to include.
Therefore, visualization for exploring is best done in such a way that
it can be iterated quickly and experimented upon, so that you can find
the signal within the noise. Software and automation are your friends
here.

Visualization for explaining is best when it is cleanest. Here, the
ability to pare down the information to its simplest form — to
strip away the noise entirely — will increase the efficiency with
which a decision maker can understand it. This is the approach to
take once you understand what the data is telling you, and you want to
communicate that to someone else. This is the kind of visualization
you should be finding in those presentations and sales
reports.

Visualization for explaining also includes infographics and other
categories of hand-drawn or custom-made images. Automated tools can be
used, but one size does not fit all.

Your customers make decisions, too

While data visualization is a powerful tool for helping you and
others within your organization make better decisions, it's important
to remember that, in the meantime, your customers are trying to decide
between you and your competitors. Many kinds of data visualization,
from complex interactive or animated graphs to brightly-colored
infographics, can help your customers explore and your customer service folks explain.

That's why all kinds of companies and organizations, from GE to Trulia to NASA, are beginning to invest
significant resources in providing interactive visualizations to their
customers and the public. This allows viewers to better understand the
company's business, and interact in a self-directed manner with the
company's expertise.

As big data becomes bigger, and more companies deal with complex
datasets with dozens of variables, data visualization will become
even more important. So far, the tide of popularity has risen more
quickly than the tide of visual literacy, and mediocre efforts abound,
in presentations and on the web.

But as visual literacy rises, thanks in no small part to impressive
efforts in major media such as The New York
Times and The
Guardian, data visualization will increasingly become a language
your customers and collaborators expect you to speak — and speak
well.

Do yourself a favor and hire a designer

It's well worth investing in a talented in-house
designer, or a team of designers. Visualization for explaining works
best when someone who understands not only the data itself, but also
the principles of design and visual communication, tailors the graph or
chart to the message.

Whether it's text or visuals, important translations require more than basic tools.

To go back to the language analogy: Google Translate is a powerful
and useful tool for giving you the general idea of what a foreign text
says. But it's not perfect, and it often lacks nuance. For getting
the overall gist of things, it's great. But I wouldn't use it to send
a letter to a foreign ambassador. For something so sensitive, and
where precision counts, it's worth hiring an experienced human
translator.

Since data visualization is like a foreign language, in the same
way, hire an experienced designer for important jobs where
precision matters. If you're making the kinds of decisions in which
your customer, product, or profit hangs in the balance, you can't
afford to base those decisions on incomplete or misleading
representations of the knowledge your company holds.

Your designer is your translator, and one of the most important
links you and your customers have to your data.

Strata 2012 — The 2012 Strata Conference, being held Feb. 28-March 1 in Santa Clara, Calif., will offer three full days of hands-on data training and information-rich sessions. Strata brings together the people, tools, and technologies you need to make data work.